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. 2022 Feb 3;12:1856. doi: 10.1038/s41598-022-05968-4

Table 3.

Univariate and multivariable logistic regression analyses for severe outcome.

Variable Univariate Multivariable p value (individual AUC vs. model AUC)
Odds ratio 95% CI p value Odds ratio 95% CI p value
Galectin-3 (binary) 7.94 (3.75–16.82) < 0.0001 3.68 (1.47–9.20)  < 0.01  < 0.001
CRP 1.11 (1.07–1.16) < 0.0001 1.05 (1.00–1.11) 0.04 0.03
Albumin 0.14 (0.06–0.33) < 0.0001 0.35 (0.13–0.89) 0.03 0.03
Critical disease (CT pulmonary affection > 50%) 7.86 (3.25–19.03) < 0.0001 4.04 (1.17–13.97) 0.03  < 0.0001
Gender (male) 1.99 (0.93–4.25) 0.08
Age 1.02 (1.00–1.05) 0.10
Diabetes 1.62 (0.74–3.57) 0.23
Hypertension 0.98 (0.48–2.01) 0.96
Obesity (BMI ≥ 30) 1.14 (0.59–2.21) 0.71
NLR 1.05 (1.02–1.09) < 0.01
Neutrophil count 1.15 (1.07–1.23) < 0.001
Ferritin 1.00 (1.07–1.23) < 0.01
Lymphocyte count 0.63 (0.28–1.42) 0.27
Platelets 1.00 (1.00–1.00) 0.89
D-Dimer 1.00 (1.00–1.00) 0.03
Fibrinogen 1.00 (1.00–1.01) < 0.01
INR 2.06 (1.01–4.24) 0.05
Triglycerides 1.01 (1.00–1.01) 0.02
AST 1.01 (1.00–1.02) 0.03

Galectin-3 was analyzed as a binary variable according to its non-linear relationship with severe outcomes (> 30.99 ng/mL = 1, < 30.99 ng/mL = 0). Only variables with a p value < 0.20 after univariate analyses were further evaluated in multivariable analyses. The AUC of the final model was compared against that of each independent predictor with DeLong’s test for correlated ROC curves. Bold values represent p < 0.05.